Location: Anywhere in LATAMWork Model: 100% RemoteEngagement: Full-time ContractorPayment: USDProject: Identity Security / Cybersecurity PlatformSeniority: SeniorLocation: Anywhere in LATAMWork Model: 100% RemoteEngagement: Full-time ContractorPayment: USDProject: Identity Security / Cybersecurity PlatformSeniority: SeniorEnglish Level: B2 / C****L - Senior DevOps Engineer (AWS/EKS/Terraform/CI/CD) · Remote · LATAMGet to Know DarwoftAt Darwoft, we build custom software solutions and partner with international companies to create high-impact digital products.We are a Latin American technology company with a people-first culture, strong professional standards, and a long-term partnership mindset.
We work with distributed teams, complex technical challenges, and clients whose technology has a direct impact on their businesses and users.About the ProjectWe are partnering with an innovative cybersecurity company developing a modern Identity Security and Identity Observability platform .
The product enables enterprise security teams to monitor identity activity, identify security gaps, detect suspicious behavi load.Build reproducible, automated ML pipelines: training, evaluation, and deployment pipelines as code, with lineage and reproducibility built in.Extend infrastructure-as-code to ML systems, using Terraform patterns and multi-project design that bring ML infrastructure under the same standards as the rest of the platform.Operate GitOps for ML workloads, owning ArgoCD configuration and promotion workflows across environments and tenants.Run ML and AI workloads on multi-tenant Kubernetes (GKE), managing GPU/accelerator scheduling, workload placement, tenant isolation, and cost-aware capacity.Own ML reliability and observability: SLOs for inference services, model and data drift detection, performance regression monitoring, alert quality, on-call ergonomics, and runbook culture.Drive ML cost efficiency by right-sizing accelerators, managing committed-use and Spot VM capacity, and attributing inference cost across tenants and workloads.Use agentic coding tools for infrastructure and pipeline work: scaffolding environments, generating and reviewing IaC and pipeline code, and accelerating automation.WHAT YOU WON'T FIND HEREA platform team that maintains the status quo.
We're actively building: new scale requirements, new architectural domains, and an ML/AI footprint that's growing fast.
Senior engineers here shape how the platform evolves, and the tools available to do it are better than they've ever been.Requirements MUST HAVE5+ years in platform engineering, SRE, MLOps, or infrastructure,



with meaningful time operating production systems at scale.Hands‐on experience deploying and operating ML or AI workloads in production: serving, inference, or training infrastructure that real users depended on.Strong SRE/DevOps foundation.
You've owned reliability for production services, defined and measured SLOs, run post‐mortems, and driven measurable improvements.Deep Terraform expertise.
You actively manage complex Terraform state, reusable modules, and multi‐project configurations in production, with CI‐driven plan/apply workflows.Strong GitOps background (ArgoCD or Flux in production).
You understand declarative infrastructure management at depth and have opinions on how to do it well.Deep Kubernetes knowledge.
You've operated clusters in production, dealt with real failure modes, and understand the system at the control plane level.
Production GKE experience (Standard and/or Autopilot) is strongly preferred.Strong GCP background: VPC networking, Compute Engine, IAM, Cloud Storage, and multi‐project/organization design.Hands‐on experience with GCP data services, especially BigQuery in production: partitioning and clustering, query cost and performance tuning, and dataset‐level IAM.
Familiarity with at least one of Dataflow, Pub/Sub, or Dataproc.Hands‐on experience building and operating CI/CD pipelines (GitHub Actions, Cloud Build, GitLab CI, or equivalent), plus an understanding of how ML pipelines differ from standard application CI/CD.Automation‐first thinking at a senior level.
You implement systems that eliminate entire categories of manual work.Active user of agentic coding tools.
You know how to direct them effectively, review their output critically, and use them to multiply your output.Strong communicator.
You can articulate operational decisions, model performance trade‐offs, and incident summaries clearly to engineers and leadership alike.NICE TO HAVEExperience with GPU/accelerator scheduling and node lifecycle management in production (e.g., GKE node auto‐provisioning, GPU time‐sharing, or equivalent).
Experience operating LLM inference at scale, managing provider quotas/throttling (TPS/TUPS), gateways, caching,



and guardrails (e.g., Vertex AI, Gemini API, or equivalent).
Experience with ML pipeline and orchestration tooling such as Argo Workflows, Kubeflow, Cloud Composer/Airflow, Vertex AI Pipelines, or equivalent.Experience with model registries, feature stores, and experiment tracking (e.g., MLflow, Feast, or equivalent).
Familiarity with model and data drift monitoring and ML‐specific obserxperience supporting highly available, production-grade cloud environments.Strong communication skills and ability to collaborate with engineering, security, QA, and business stakeholders.High degree of autonomy, ownership, and analytical problem-solving ability.Bachelor's degree in Computer Science, Software Engineering, Systems Engineering, or a related technical discipline, or equivalent professional experience.Core Technology StackYou'll work with technologies including:AWSKubernetes / EKSDockerTerraformAnsibleGitHub ActionsJenkinsLinuxPythonBashPrometheusGrafanaCloudWatchOpenSearch / ElasticsearchNice to HaveExperience with HashiCorp Nomad .
Experience with HashiCorp Consul .
Broader experience with the HashiCorp ecosystem.Experience operating Kafka in production.Experience supporting data infrastructure based on:ClickHouseElasticsearchMongoDBRedisExperience with distributed systems and high-volume data platforms.Previous experience in cybersecurity, identity security, or security SaaS platforms .
Experience working with cloud security controls and compliance frameworks.Experience with FinOps and cloud cost optimization .
Experience designing internal developer platforms or platform engineering capabilities.Exposure to infrastructure supporting AI/ML or LLM-based applications .
What Success Looks LikeSuccess in this role means:Increasing infrastructure reliability and availability.Reducing deployment friction and improving engineering velocity.Increasing infrastructure automation and reducing manual operational work.Improving observability and reducing mean time to detection and resolution.Operating Kubernetes workloads reliably at scale.Strengthening security throughout cloud infrastructure and deployment processes.Improving AWS cost efficiency without compromising reliability.Contributing reusable platform capabilities that allow engineering teams to move faster.Continuously improving production readiness as the platform scales.What Darwoft OffersContractor agreement with payment in USD100% remote workArgentina's public holidaysEnglish classesReferral programAccess to learning platforms
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📌 Devops Engineer - Infra Automation & Secure Deployments (Córdoba)
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